* Codes to replicate the regression analyses in the main text




***********
* Table 1 *
***********

* Model 1
cluster2 log_personalpronoun_name_prop2 Iadjust, fcluster(candidateID) tcluster(dyID)

*Linear regression with 2D clustered SEs                Number of obs =    7488
*                                                       F(  1,  7486) =   94.68
*                                                       Prob > F      =  0.0000
*Number of clusters (candidateID) =  3280               R-squared     =  0.0136
*Number of clusters (dyID) =    1888                    Root MSE      =  0.9184
*------------------------------------------------------------------------------
*log_person.. |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
*-------------+----------------------------------------------------------------
*     Iadjust |   .1310257   .0192418     6.81   0.000     .0933063    .1687451
*       _cons |   -5.35697   .0141371  -378.93   0.000    -5.384683   -5.329257
*------------------------------------------------------------------------------


* Model 2
cluster2 log_personalpronoun_name_prop2 Iadjust gender age incumbent log_totwin log_distpopulation distpop65 log_distprimary, fcluster(candidateID) tcluster(dyID)

*Linear regression with 2D clustered SEs                Number of obs =    7424
*                                                       F(  8,  7415) =   45.46
*                                                       Prob > F      =  0.0000
*Number of clusters (candidateID) =  3271               R-squared     =  0.0418
*Number of clusters (dyID) =    1869                    Root MSE      =  0.9048
*------------------------------------------------------------------------------------
*log_person~e_prop2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
*-------------------+----------------------------------------------------------------
*           Iadjust |    .067773    .015533     4.36   0.000     .0373239    .0982221
*            gender |  -.0302941   .0389853    -0.78   0.437    -.1067164    .0461282
*               age |  -.0017744   .0012508    -1.42   0.156    -.0042264    .0006775
*         incumbent |  -.1012012   .0355425    -2.85   0.004    -.1708746   -.0315278
*        log_totwin |   .0951439   .0256752     3.71   0.000     .0448132    .1454747
*log_distpopulation |   .2441175   .0296922     8.22   0.000     .1859124    .3023226
*         distpop65 |  -1.028813   .2750447    -3.74   0.000    -1.567978   -.4896471
*   log_distprimary |   .0205914   .0089197     2.31   0.021     .0031062    .0380766
*             _cons |  -8.258962   .4217474   -19.58   0.000    -9.085707   -7.432218
*------------------------------------------------------------------------------------


* Model 3
cluster2 log_partyname_prop2 Iadjust, fcluster(candidateID) tcluster(dyID)

*Linear regression with 2D clustered SEs                Number of obs =    7488
*                                                       F(  1,  7486) =  130.31
*                                                       Prob > F      =  0.0000
*Number of clusters (candidateID) =  3280               R-squared     =  0.0164
*Number of clusters (dyID) =    1888                    Root MSE      =  1.2189
*------------------------------------------------------------------------------
*log_partyn~2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
*-------------+----------------------------------------------------------------
*     Iadjust |  -.1910244    .026519    -7.20   0.000    -.2430091   -.1390398
*       _cons |   -5.49726   .0193508  -284.08   0.000    -5.535193   -5.459327
*------------------------------------------------------------------------------


* Model 4
cluster2 log_partyname_prop2 Iadjust gender age incumbent log_totwin log_distpopulation distpop65 log_distprimary, fcluster(candidateID) tcluster(dyID)

*Linear regression with 2D clustered SEs                Number of obs =    7424
*                                                       F(  8,  7415) =  144.69
*                                                       Prob > F      =  0.0000
*Number of clusters (candidateID) =  3271               R-squared     =  0.1273
*Number of clusters (dyID) =    1869                    Root MSE      =  1.1482
*------------------------------------------------------------------------------------
*log_partyname_pr~2 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
*-------------------+----------------------------------------------------------------
*           Iadjust |  -.1581022   .0243381    -6.50   0.000    -.2058117   -.1103927
*            gender |   .2787556   .0603068     4.62   0.000     .1605372     .396974
*               age |    .018228   .0016993    10.73   0.000     .0148969     .021559
*         incumbent |  -.1236484   .0391173    -3.16   0.002    -.2003294   -.0469675
*        log_totwin |  -.4702319   .0313977   -14.98   0.000    -.5317803   -.4086836
*log_distpopulation |   .2129195   .0334477     6.37   0.000     .1473525    .2784864
*         distpop65 |  -1.014385   .3041458    -3.34   0.001    -1.610597   -.4181729
*   log_distprimary |   .0170389   .0114882     1.48   0.138    -.0054812    .0395589
*             _cons |  -8.605433   .4751188   -18.11   0.000      -9.5368   -7.674065
*------------------------------------------------------------------------------------
